Automated assessment of the mouse body-language reveals pervasive behavioral disruption in a two-hit model of psychiatric vulnerability

Abstract

The influence of early-life experiences is widely acknowledged as a crafting tool that sculpts complex behavioral patterns and well-being of living organisms. The use of preclinical models can provide invaluable insight into how a negative environmental push interplays with genetic make-up in shaping psychiatric vulnerability. However, the assessment of psychiatric traits in cross-species studies often relies on the use of surrogate metrics as a proxy for the internal state, limiting the interpretation to context-dependent outcomes. In this work, we exploited a validated computational tool for digitalized ethological screening to identify spontaneous hallmarks of altered behavioral functioning in a dual-hit mouse model of psychiatric vulnerability. To do so, mice carrying heterozygous deletion of the gene coding for Contactin-associated protein-like 2 (Cntnap2+/-) and their wild-type (WT) littermates were raised with limited bedding and nesting (LBN). These animals were compared to both WT and Cntnap2+/- mice raised in standard conditions, mapping their spontaneous behavior during freely-moving exploration. Our data show that descriptors of motility state or surrogate anxiety indicators largely failed in detecting subtle diversion from control conditions. By contrast, automated segmentation of the body-language revealed a significant impact of both genotype and early-life experience in shaping the spontaneous behavioral programming. Thus, using unsupervised clustering, we unveiled two alternative neurobehavioral profiles within our dataset. We found that one of the identified profiles largely overlapped with Cntnap2+/- mice raised with LBN, while the other was equally shared among controls. We conclude that the coincidence of early-life adversity and Cntnap2 haploinsufficiency drastically reshapes behavioral structure in rodents. SIGNIFICANCE STATEMENTEnhancing the predictive and face validity of preclinical models in psychiatric research remains a significant challenge due to the inherent heterogeneity and complexity of these conditions. While animal models are crucial for understanding the risk factors involved, replicating the full complexity of these conditions continues to pose difficulties. In this study, we use a tool for digitalized behavioral screening to investigate emotional hallmarks in a double-hit (environmental and genetic) mouse model of vulnerability for psychiatric disorder, glimpsing subliminal behavioral disturbances not captured with traditional assessments. Our findings highlight the effectiveness of novel computational tools in identifying subtle behavioral deviations and support the hypothesis that gene-environment interaction contributes to shape alternative behavioral structure in mice.